Literature DB >> 25392421

MiCroKiTS 4.0: a database of midbody, centrosome, kinetochore, telomere and spindle.

Zhengnan Huang1, Lili Ma1, Yongbo Wang1, Zhicheng Pan1, Jian Ren2, Zexian Liu3, Yu Xue4.   

Abstract

We reported an updated database of MiCroKiTS 4.0 (http://microkit.biocuckoo.org) for proteins temporally and spatially localized in distinct subcellular positions including midbody, centrosome, kinetochore, telomere and mitotic spindle during cell division/mitosis. The database was updated from our previously developed database of MiCroKit 3.0, which contained 1489 proteins mostly forming super-complexes at midbody, centrosome and kinetochore from seven eukaryotes. Since the telomere and spindle apparatus are critical for cell division, the proteins localized at the two positions were also integrated. From the scientific literature, we curated 1872 experimentally identified proteins which at least locate in one of the five positions from eight species. Then the ortholog detection was performed to identify potential MiCroKiTS proteins from 144 eukaryotic organisms, which contains 66, 45 and 33 species of animals, fungi and plants, respectively. In total, 87,983 unique proteins with corresponding localization information were integrated into the database. The primary references of experimentally identified localizations were provided and the fluorescence microscope figures for the localizations of human proteins were shown. The orthologous relations between predicted and experimental localizations were also present. Taken together, we anticipate the database can serve as a useful resource for further analyzing the molecular mechanisms during cell division.
© The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Entities:  

Mesh:

Substances:

Year:  2014        PMID: 25392421      PMCID: PMC4383938          DOI: 10.1093/nar/gku1125

Source DB:  PubMed          Journal:  Nucleic Acids Res        ISSN: 0305-1048            Impact factor:   16.971


INTRODUCTION

In eukaryotic cells, a large number of proteins spatially and temporally localize at distinct subcellular positions and organize various super-complexes to orchestrate the chromosome segregation during cell division/mitosis (1). For example, the centrosome of animal cells, the spindle pole body in budding yeast and homologous structures in other species contain hundreds of proteins and act as the microtubule-organizing center (MTOC) (Figure 1) (2–5). Besides the nucleation and organization of microtubules and mitotic/meiotic spindles for attaching chromosomes during mitosis or meiosis, centrosome also plays critical roles in a variety of biological processes, such as primary cilia formation (4,5) and intracellular trafficking (4,5). The aberrance of centrosome or centrosomal proteins has been involved in the misregulation of cell cycle, genetic diseases (6) and cancers (7). For example, Lingle et al. found that the centrosomal amplification is highly associated with chromosomal instability (CIN) and may participate in breast tumor development and progression (8). Also, the tight interactions between microtubules and chromosomes are mediated by centromere via the attachment site kinetochore, which contains hundreds of proteins forming in super-complexes (Figure 1) (9). Centromere/kinetochore transmits the power from spindle microtubules for the chromosome movement (10), and serve as the checkpoint for cell division control to ensure all sister chromatids can be correctly and averagely delivered into daughter cells (11). The aberrance of centromere/kinetochore generates missegregation of chromosomes, CIN and anaphase lagging chromosomes (12,13), which are frequently observed in cancer cells (13,14). In addition, as the final stage of cell division, cytokinesis comprises a number of complicated processes including the average distribution of intracellular contents and the separation of two daughter cells (15–18). Numerous proteins are involved in cytokinesis through the cooperation in midbody/cleavage furrow, for which the conserved structures in yeast and plants are bud neck and phragmoplast, respectively (Figure 1) (18,19). Obviously, cytokinesis is critical for cell division, while the failure of this process might be involved in cancers (20). Taken together, a comprehensive identification of proteins located at centrosome, kinetochore and/or midbody is critical for further understanding the molecular mechanisms of cell division/mitosis.
Figure 1.

The schematic diagram for the five subcellular positions including midbody/cleavage furrow/bud neck/phragmoplast, centrosome/spindle pole body, kinetochore/centromere, telomere and spindle apparatus in eukaryotic cells.

The schematic diagram for the five subcellular positions including midbody/cleavage furrow/bud neck/phragmoplast, centrosome/spindle pole body, kinetochore/centromere, telomere and spindle apparatus in eukaryotic cells. Besides the distribution of mother cell contents equally into two daughter cells, the preservation of the chromosomal integrity and stability is also critical for cell cycle (21). As an intrinsic ‘mitotic clock’, telomere monitors the chromosome end-replication to ensure its length through the interactions of numerous proteins with telomeric DNA sequences (22,23). The aberrance of telomere is highly associated with various human diseases, such as ageing syndromes and cancers (24–26). For example, the shortened telomeres are associated with Werner Syndrome, a premature aging syndrome (27), whereas Chin et al. identified that transition through telomere crisis is crucial for the progression of breast cancers (28). A number of proteins located at midbody, centrosome or kinetochore can also translocate at telomere. For example, tankyrase, a human poly(ADP-ribose) polymerase, locates at centrosomes in mitosis, but colocalizes with a telomeric regulator TRF1 at telomeres during interphase (29). Also, two spindle assembly checkpoint proteins BubR1 and Mad2 can localize at kinetochore, but also colocalize with TRF1 at telomeres during mitosis, and form a link between the mitotic spindle and telomeres (30). Moreover, an E3 ubiquitin ligase Rnf8 localizes at midbody during cytokinesis (31), but can also translocate to uncapped telomeres for the chromosome end protection (32). Given the tight associations of telomere with midbody, centrosome and kinetochore, a systematic collection of telomeric proteins can provide helpful information for further studies on cell cycle and human health. In addition, a number of microtubule-associated proteins dispersedly localize at the spindle apparatus but not limited to centrosome or kinetochore. For example, a proteomic analysis together with further immunofluorescence assays identified at least six spindle proteins (33). Also, a Mad2 homolog, MAD2B, interacts and colocalizes with the clathrin light chain A at the mitotic spindle (34). Thus, the integration of mitotic/meiotic spindle proteins can also be helpful for further understanding the cell division. With numerous experimental studies carried out to dissect the proteins localized in these subcellular positions, a handful of computational efforts have also been contributed. For example, the Cildb database was developed by Arnaiz et al. for centrosome and cilia proteins (35), while Nogales-Cadenas et al. constructed the CentrosomeDB database for human centrosomal proteins (36) and Alves-Cruzeiro et al. updated it to contain centrosomal proteins in Drosophila melanogaster (37). We also developed the MiCroKit database to maintain the proteins which were identified to localize in positions including centrosome, kinetochore and midbody for seven model organisms (38). Besides the database constructions, computational predictions and analyses were also performed. For example, Chen et al. developed the MicekiPred software to predict potential midbody, centrosome and kinetochore proteins (39), while recently Kuhn et al. and Azimzadeh et al. analyzed the evolutionary history of centrosome proteins (40,41). Furthermore, our computational studies showed that the positions including midbody, centrosome and kinetochore enriched KEN-box and D-box proteins (42), and the proteins regulated by Polo-like kinases (Plks) through phosphorylation and phospho-binding (43). In this study, we greatly improved the MiCroKit 3.0 database through extending the types of localizations including spindle apparatus and telomere, and developed the MiCroKiTS (Midbody, Centrosome, Kinetochore, Telomere and Spindle) 4.0 database. From literature, we manually collected 1872 MiCroKiTS proteins among eight model organisms, which were two fungi including Saccharomyces cerevisiae and Schizosaccharomyces pombe, five animals including Caenorhabditis elegans, D. melanogaster, Xenopus laevis, Mus musculus and Homo sapiens and one plant Arabidopsis thaliana. Furthermore, based on the conception that orthologs among different organisms might share similar localizations in these subcellular positions, the orthologs for the experimentally identified MiCroKiTS proteins among 144 eukaryotes including 66 animals, 45 Fungi and 33 plants were detected. All the experimentally identified MiCroKiTS proteins and their orthologs were integrated into the MiCroKiTS 4.0 database, which contains 87 983 proteins in total. The source references, ortholog relationships and other annotations were provided for MiCroKiTS proteins in the database. Taken together, the MiCroKiTS 4.0 database could serve as a useful data resource for further studies of the molecular mechanisms for cell division.

CONSTRUCTION AND CONTENT

In this study, we defined the MiCroKiTS proteins as the proteins which have localizations in any of the subcellular positions including centrosome/spindle pole body, kinetochore/centromere, mitotic/meiotic spindle, midbody/cleavage furrow and telomere. To construct a reliable data resource, we manually curated the experimentally identified MiCroKiTS proteins from literatures (published before 1 June 2014 in PubMed) in eight model organisms, which were two fungi including S. cerevisiae and S. pombe, five animals including C. elegans, D. melanogaster, X. laevis, M. musculus and H. sapiens, and one plant A. thaliana. With the rationale established previously (38), only the proteins which were unambiguously observed to be localized at these super-complexes under fluorescent microscope were collected. To collect the MiCroKiTS proteins, a number of keywords were employed to search the literature in PubMed. For centrosome/spindle pole body, kinetochore/centromere, midbody/cleavage furrow, the keywords were adopted as previously described (38), while additional keywords were considered for plants. For example, the terms ‘MTOC’ and ‘phragmoplast’ were used to search similar structures for centrosome and midbody in plants, respectively. For spindle apparatus and telomere, the keywords ‘spindle’ and ‘telomere’ were employed. To simplify the descriptions in this study, the terms ‘centrosome’, ‘kinetochore’, ‘midbody’, ‘spindle’ and ‘telomere’ were used to representing these super-complexes and similar structures. In total, we collected 1872 MiCroKiTS proteins, which contain 2277 experimentally identified localizations. In comparison with MiCroKit 3.0 database, 383 new proteins and 508 newly reported localizations of both previously collected and new proteins were added. Furthermore, to provide an intuitive presentation for MiCroKiTS localizations, the first published fluorescence evidence for localizations of human MiCroKiTS proteins were obtained from the literature. To provide information for species beyond the eight model organisms, homologous detections were performed to search orthologs, which might be potential MiCroKiTS proteins and could be helpful for further studies of these super-complexes. The reference proteomes from 143 genome-sequenced eukaryotes including 65 animals, 45 fungi and 33 plants were downloaded from Ensembl database (44), while the reference proteome of X. laevis was unavailable. As previously described (38,45,46), the strategy of reciprocal best hits (47) with Basic Local Alignment Search Tool (BLAST) package (48) were employed to detect orthologs of MiCroKiTS proteins from the eight model organisms in other species. Based on the concept that orthologs might have similar localizations in these subcellular positions, the localizations of orthologs were predicted as the homologous experimentally identified MiCroKiTS proteins. In total, 86 111 orthologs were predicted as potential MiCroKiTS proteins, which were also integrated into the MiCroKiTS 4.0 database. The numbers of proteins with different localizations among different organisms were summarized in Supplementary Table S1. All the proteins in the database were annotated with source references and other annotations from UniProt database (49) to provide brief introductions. All localizations and sequences of proteins in MiCroKiTS were available for download at http://microkit.biocuckoo.org/download.php.

USAGE

To provide convenient usage, the MiCroKiTS 4.0 database web interface was designed in a user-friendly manner for search and browse. The website contains four search options including one/multiple keywords-based simple search (Figure 2A), ‘Advanced search’ based on a combination of multiple keywords (Figure 2B), multiple keywords based ‘Batch search’ (Figure 2C) and protein sequence-based ‘BLAST search’ (Figure 2D). For example, if a keyword ‘aurora’ in ‘Any Field’ was submitted for a simple search (Figure 2A), the website will return a list of MiCroKiTS proteins, such as Aurora kinase B from H. sapiens in a tabular format with accession, species, and protein/gene names/aliases (Figure 2E). By clicking the accession ‘Q96GD4’, user could visit the webpage of human Aurora kinase with detailed annotation including localizations, PubMed IDs of source references and the orthologs (Figure 2F). For human MiCroKiTS proteins, the representing fluorescent microscope figures were provided by clicking the ‘Show Figures’ (Figure 2F). Furthermore, two terms specified in two areas and combined with operators of ‘and’, ‘or’ and ‘exclude’ could be employed to perform a complex query in ‘Advanced Search’ (Figure 2B). For example, querying the database with ‘human’ in ‘Species’ and ‘aurora’ in ‘Gene/Protein Name’ will return three human aurora kinases (Figure 2B). Alternatively, user could submit a list of keywords to perform a batch search. For example, three human aurora kinases could be retrieved by submitting the list of their UniProt accessions (Figure 2C). Furthermore, user could submit a protein sequence in FASTA format in ‘BLAST Search’ to find homologous MiCroKiTS proteins (Figure 2D). For example, the sequence of human Aurora kinase B could be input in the FASTA format to search homologous proteins in the database. The ‘Advanced Search’, ‘Batch search’ and ‘BLAST Search’ will return the list of searching hits in a tabular format as the simple search (Figure 2E). In addition, there is a checkbox of ‘ONLY experimentally identified MiCroKiTS proteins’ for each search option (Figure 2). If the checkbox is selected, only experimentally identified MiCroKiTS proteins will be queried.
Figure 2.

The search options of MiCroKiTS database. (A) The database can be directly queried with one or multiple keywords. (B) The ‘Advanced search’ option allows users to submit a combination of two terms for searching. (C) The database could be searched to retrieve a list of proteins through submitting a list of keywords such as UniProt accessions. (D) The database can be queried with a protein sequence in FASTA format to find identical or homologous proteins. (E) The protein list derived from the search options. (F) The details of the MiCroKiTS protein Aurora kinase B in H. sapiens, while the fluorescence microscope figure for the localizations can also be visualized.

The search options of MiCroKiTS database. (A) The database can be directly queried with one or multiple keywords. (B) The ‘Advanced search’ option allows users to submit a combination of two terms for searching. (C) The database could be searched to retrieve a list of proteins through submitting a list of keywords such as UniProt accessions. (D) The database can be queried with a protein sequence in FASTA format to find identical or homologous proteins. (E) The protein list derived from the search options. (F) The details of the MiCroKiTS protein Aurora kinase B in H. sapiens, while the fluorescence microscope figure for the localizations can also be visualized. For convenient browse in MiCroKiTS database, we developed three options including single localization-based browse, multiple localizations-based browse and browse by species. For example, through clicking the ‘Centrosome’ in the single localization browse option (Figure 3A), the distribution of centrosome proteins among organisms was returned (Figure 3B), while centrosomal proteins, such as Aurora kinase B from H. sapiens were listed after further clicking the species name ‘Homo sapiens (Human)’ (Figure 3C). Furthermore, the multiple localizations-based browse option enable users to find the proteins localized in all the selected subcellular positions (Figure 3D). For example, if the checkboxes of centrosome, kinetochore and midbody were selected (Figure 3D), the MiCroKiTS proteins localized in all the three subcellular positions among different organisms were shown (Figure 3E). These proteins could be listed through clicking the species name (Figure 3F). Alternatively, the MiCroKiTS database could be browsed by organisms. For example, after clicking the ‘Homo sapiens (Human)’ in the list (Figure 3G), the distribution of human MiCroKiTS proteins in the subcellular regions was shown (Figure 3H), while the human midbody proteins, such as Aurora kinase B, could be listed through clicking ‘Midbody’ (Figure 3I). Again, the checkboxes of ‘ONLY experimentally identified MiCroKiTS proteins’ were provided for exclusively browsing the experimentally identified MiCroKiTS proteins (Figure 2A, D and G).
Figure 3.

The MiCroKiTS database can be browsed by either localizations or by species. (A) Browse by single localization. (B) The distribution of centrosomal proteins in different organisms. (C) The list of centrosomal proteins in H. sapiens. (D) The proteins with multiple localizations can also be browsed. (E) For example, the distribution of proteins located at centrosome, kinetochore and midbody among different organisms can be shown. (F) The list of proteins located in all of the three positions in H. sapiens. (G) Browse by species. (H) The distribution of human MiCroKiTS proteins in different subcellular positions. (I) The list of midbody proteins in H. sapiens.

The MiCroKiTS database can be browsed by either localizations or by species. (A) Browse by single localization. (B) The distribution of centrosomal proteins in different organisms. (C) The list of centrosomal proteins in H. sapiens. (D) The proteins with multiple localizations can also be browsed. (E) For example, the distribution of proteins located at centrosome, kinetochore and midbody among different organisms can be shown. (F) The list of proteins located in all of the three positions in H. sapiens. (G) Browse by species. (H) The distribution of human MiCroKiTS proteins in different subcellular positions. (I) The list of midbody proteins in H. sapiens.

DISCUSSION

During cell division, a large number of proteins are transiently recruited to distinct subcellular positions, such as midbody/cleavage furrow, centrosome/spindle pole body, kinetochore/centromere, mitotic/meiotic spindle and telomere, and assemble various protein super-complexes for orchestrating the segregation of cell contents into daughter cells (2–5,9–11,15–18,50–58). These proteins play critical roles in various cellular processes, while their aberrances were heavily related with diseases and cancers (6,7,12,20,24–26,53). Thus, systematic dissecting the proteins localized in these positions will be helpful for further understanding their functional roles and regulatory mechanisms. In this study, we updated the database of MiCroKit 3.0 into MiCroKiTS 4.0 for more organisms and more types of subcellular positions including spindle apparatus and telomere. In total, 1872 experimentally identified MiCroKiTS proteins with 2277 localizations were collected in eight model organisms. Furthermore, homologous detections were performed to find orthologs in species beyond the eight model organisms for experimentally identified MiCroKiTS proteins to search potential MiCroKiTS proteins, which were also integrated into the database. The distribution of proteins in centrosome, kinetochore, spindle apparatus, midbody and telomere were summarized and presented in Figure 4. Because the reference proteome for X. laevis was unavailable, only known MiCroKiTS proteins were collected (Figure 4). From the result, it was observed that the centrosome has most proteins, while there were more proteins localized in kinetochore and midbody than spindle apparatus and telomere (Figure 4). Also, the numbers of MiCroKiTS proteins per localization vary greatly among different kingdoms, but are similar in the same kingdom (Figure 4). However, further experimental studies are still needed to verify the observations, while orthologs among distantly related species, such as organisms in different kingdoms, should be carefully considered. Taken together, here we updated the MiCroKit 3.0 database, which only contains proteins for three super-complexes in seven organisms, to MiCroKiTS 4.0 database for subcellular positions in 144 species. We believed that the update will make the database more helpful for the further computational or experimental studies. The MiCroKiTS database will be routinely updated to maintain more information for systematic understanding of the molecular mechanisms and function roles of the MiCroKiTS proteins during cell cycle.
Figure 4.

The heatmap about the distribution of MiCroKiTS proteins in the MiCroKiTS 4.0 database for different localizations among 144 eukaryotic species from different kingdoms. The upper part was the results for the 66 animals, and the lower section was the results for the 33 plants and 45 fungi.

The heatmap about the distribution of MiCroKiTS proteins in the MiCroKiTS 4.0 database for different localizations among 144 eukaryotic species from different kingdoms. The upper part was the results for the 66 animals, and the lower section was the results for the 33 plants and 45 fungi.

SUPPLEMENTARY DATA

Supplementary Data are available at NAR Online.
  57 in total

Review 1.  Spindle assembly in animal cells.

Authors:  D A Compton
Journal:  Annu Rev Biochem       Date:  2000       Impact factor: 23.643

Review 2.  Exploring the evolutionary history of centrosomes.

Authors:  Juliette Azimzadeh
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2014-09-05       Impact factor: 6.237

Review 3.  Cytokinesis in eukaryotes.

Authors:  David A Guertin; Susanne Trautmann; Dannel McCollum
Journal:  Microbiol Mol Biol Rev       Date:  2002-06       Impact factor: 11.056

4.  Cildb: a knowledgebase for centrosomes and cilia.

Authors:  Olivier Arnaiz; Agata Malinowska; Catherine Klotz; Linda Sperling; Michal Dadlez; France Koll; Jean Cohen
Journal:  Database (Oxford)       Date:  2009-12-07       Impact factor: 3.451

5.  TRF1 controls telomere length and mitotic fidelity in epithelial homeostasis.

Authors:  Purificacion Muñoz; Raquel Blanco; Guillermo de Carcer; Stefan Schoeftner; Roberta Benetti; Juana M Flores; Marcos Malumbres; Maria A Blasco
Journal:  Mol Cell Biol       Date:  2009-01-05       Impact factor: 4.272

Review 6.  The spindle-assembly checkpoint in space and time.

Authors:  Andrea Musacchio; Edward D Salmon
Journal:  Nat Rev Mol Cell Biol       Date:  2007-04-11       Impact factor: 94.444

7.  GPS-ARM: computational analysis of the APC/C recognition motif by predicting D-boxes and KEN-boxes.

Authors:  Zexian Liu; Fang Yuan; Jian Ren; Jun Cao; Yanhong Zhou; Qing Yang; Yu Xue
Journal:  PLoS One       Date:  2012-03-29       Impact factor: 3.240

8.  Coiled-coil proteins facilitated the functional expansion of the centrosome.

Authors:  Michael Kuhn; Anthony A Hyman; Andreas Beyer
Journal:  PLoS Comput Biol       Date:  2014-06-05       Impact factor: 4.475

9.  Genome stability is ensured by temporal control of kinetochore-microtubule dynamics.

Authors:  Samuel F Bakhoum; Sarah L Thompson; Amity L Manning; Duane A Compton
Journal:  Nat Cell Biol       Date:  2008-12-07       Impact factor: 28.824

10.  UUCD: a family-based database of ubiquitin and ubiquitin-like conjugation.

Authors:  Tianshun Gao; Zexian Liu; Yongbo Wang; Han Cheng; Qing Yang; Anyuan Guo; Jian Ren; Yu Xue
Journal:  Nucleic Acids Res       Date:  2012-11-20       Impact factor: 16.971

View more
  11 in total

1.  Proteomic Profiling of Microtubule Self-organization in M-phase.

Authors:  Miquel Rosas-Salvans; Tommaso Cavazza; Guadalupe Espadas; Eduard Sabido; Isabelle Vernos
Journal:  Mol Cell Proteomics       Date:  2018-07-03       Impact factor: 5.911

2.  The Clathrin-dependent Spindle Proteome.

Authors:  Sushma R Rao; Neftali Flores-Rodriguez; Scott L Page; Chin Wong; Phillip J Robinson; Megan Chircop
Journal:  Mol Cell Proteomics       Date:  2016-05-12       Impact factor: 5.911

3.  THANATOS: an integrative data resource of proteins and post-translational modifications in the regulation of autophagy.

Authors:  Wankun Deng; Lili Ma; Ying Zhang; Jiaqi Zhou; Yongbo Wang; Zexian Liu; Yu Xue
Journal:  Autophagy       Date:  2018       Impact factor: 16.016

Review 4.  Midbody: from cellular junk to regulator of cell polarity and cell fate.

Authors:  Lai Kuan Dionne; Xiao-Jing Wang; Rytis Prekeris
Journal:  Curr Opin Cell Biol       Date:  2015-05-15       Impact factor: 8.382

5.  KinetochoreDB: a comprehensive online resource for the kinetochore and its related proteins.

Authors:  Chen Li; Steve Androulakis; Ashley M Buckle; Jiangning Song
Journal:  Database (Oxford)       Date:  2016-03-17       Impact factor: 3.451

6.  CGDB: a database of circadian genes in eukaryotes.

Authors:  Shujing Li; Ke Shui; Ying Zhang; Yongqiang Lv; Wankun Deng; Shahid Ullah; Luoying Zhang; Yu Xue
Journal:  Nucleic Acids Res       Date:  2016-10-26       Impact factor: 16.971

7.  Phosphatidylinositol-5-phosphate 4-kinase gamma accumulates at the spindle pole and prevents microtubule depolymerization.

Authors:  Tz-Chi Lin; Hsiao-Hui Kuo; Yi-Chen Wu; Tiffany S Pan; Ling-Huei Yih
Journal:  Cell Div       Date:  2019-08-21       Impact factor: 5.130

8.  Secreted midbody remnants are a class of extracellular vesicles molecularly distinct from exosomes and microparticles.

Authors:  Alin Rai; David W Greening; Rong Xu; Maoshan Chen; Wittaya Suwakulsiri; Richard J Simpson
Journal:  Commun Biol       Date:  2021-03-25

9.  PP2A-B' holoenzyme substrate recognition, regulation and role in cytokinesis.

Authors:  Cheng-Guo Wu; Hui Chen; Feng Guo; Vikash K Yadav; Sean J Mcilwain; Michael Rowse; Alka Choudhary; Ziqing Lin; Yitong Li; Tingjia Gu; Aiping Zheng; Qingge Xu; Woojong Lee; Eduard Resch; Benjamin Johnson; Jenny Day; Ying Ge; Irene M Ong; Mark E Burkard; Ylva Ivarsson; Yongna Xing
Journal:  Cell Discov       Date:  2017-08-08       Impact factor: 10.849

10.  TelNet - a database for human and yeast genes involved in telomere maintenance.

Authors:  Delia M Braun; Inn Chung; Nick Kepper; Katharina I Deeg; Karsten Rippe
Journal:  BMC Genet       Date:  2018-05-18       Impact factor: 2.797

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.